NicheNet: modeling intercellular communication by linking ligands to target genes

Computational methods that model how gene expression of a cell is influenced by interacting cells are lacking. We present NicheNet (https://github.com/saeyslab/nichenetr), a method that predicts ligand-target links between interacting cells by combining their expression data with prior knowledge on signaling and gene regulatory networks. We applied NicheNet to tumor and immune cell microenvironment data and demonstrate that NicheNet can infer active ligands and their gene regulatory effects on interacting cells. NicheNet uses expression data, in combination with a previous model built on known signaling and gene regulatory networks, to predict ligand-target links in cell-to-cell communications.